Engineering of Smart Agriculture—2nd Edition

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Agricultural Science and Technology".

Deadline for manuscript submissions: 16 December 2024 | Viewed by 1383

Special Issue Editors


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Guest Editor
Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka 116, Kraków, Poland
Interests: machine management in agriculture; ergonomics in agricultural technology; electromagnetic identification of plant quality structure; soil type; subsoil compaction; agricultural engineering; electromagnetism
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Guest Editor
Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Krakow, Poland
Interests: agricultural microbiology; agrobiotechnology; precision agriculture; nanotechnology; electromagnetic effects on microorganisms and ergonomics

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Guest Editor
Faculty of Production and Power Engineering, University of Agriculture in Krakow, Balicka 116, Kraków, Poland
Interests: earth and environmental sciences; geophysical methods; ground penetrating radar (GPR); electrical and electromagnetic; magnetic and gravity; seismic refraction and reflections; soil properties assessments; precision agriculture

Special Issue Information

Dear Colleagues,

Modern agricultural production has two main tasks that now must coexist. The first is yield maximization in order to satisfy market needs, and the second is minimization of the interference with the soil environment. One of the basic criteria of a balance between these tasks is the degree of soil biological improvement, the parameterization of which is an important issue in modern production systems. Among the innovative technologies that have been developed in the last few decades, precision agriculture can be considered the most important; it is considered to be an excellent tool for the development of sustainable agriculture and allows us to optimize production for present and future generations while taking into account economic, ecological, and social aspects. This concept was born from the conviction that the variability in plant growth conditions is the factor that contributes most to the variability in yields at the field scale and, therefore, it would be advantageous to adapt the amount of input to the local soil conditions and to perform the right treatment in the right place at the right time. A very important issue is the search for the most effective methods that will allow us to delineate in the field areas differing in production conditions, among which soil properties are the most important. A number of technologically advanced devices have been developed, thanks to which large amounts of data can be acquired in real time under field conditions in a continuous measurement mode using proximity detection. Modern technical solutions allow for the integration of satellite-based surface condition identification systems with ground-based systems and aircraft. Integrating various measurements into a single system for mapping soil properties is a current research problem. It is predicted that geophysical surveys with the simultaneous use of more sensors will become the standard because of the broad range of field information necessary for proper management. Modern farm and production technologies are monitored through the use of telematic systems and software that allow for real-time analysis and then simulation of the economic outcome of a given activity or process, which consequently leads to its optimization. In addition, networking of the entire machine park enables us to automatically plan maintenance services.

Dr. Paweł Kiełbasa
Dr. Anna Miernik
Dr. Akinniyi Akinsunmade
Guest Editors

Manuscript Submission Information

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Keywords

  • precision agriculture
  • telematics
  • geoinformatics
  • agricultural production technology
  • measurement systems
  • agricultural engineering
  • mechanical engineering
  • geophysics
  • soil
  • plant

Published Papers (1 paper)

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Research

17 pages, 5111 KiB  
Article
Modelling Specific Energy Requirement for a Power-Operated Vertical Axis Rotor Type Intra-Row Weeding Tool Using Artificial Neural Network
by Satya Prakash Kumar, V. K. Tewari, Abhilash Kumar Chandel, C. R. Mehta, C. M. Pareek, C. R. Chethan and Brajesh Nare
Appl. Sci. 2023, 13(18), 10084; https://doi.org/10.3390/app131810084 - 07 Sep 2023
Cited by 1 | Viewed by 963
Abstract
Specific energy prediction is critically important to enhance field performance of agricultural implements. It enables optimal utilization of tractor power, reduced inefficiencies, and identification of comprehensive inputs for designing energy-efficient implements. In this study, A 3-5-1 artificial neural network (ANN) model was developed [...] Read more.
Specific energy prediction is critically important to enhance field performance of agricultural implements. It enables optimal utilization of tractor power, reduced inefficiencies, and identification of comprehensive inputs for designing energy-efficient implements. In this study, A 3-5-1 artificial neural network (ANN) model was developed to estimate specific energy requirement of a vertical axis rotor type intra-row weeding tool. The depth of operation in soil bed, soil cone index, and forward/implement speed ratio (u/v) were selected as the input variables. Soil bin investigations were conducted using the vertical axis rotor (RVA), interfaced with draft, torque, speed sensors, and data acquisition system to record dynamic forces employed during soil–tool interaction at ranges of different operating parameters. The depth of operation (DO) had the maximum influence on the specific energy requirement of the RVA, followed by the cone index (CI) and the u/v ratio. The developed ANN model was able to predict the specific energy requirements of RVA at high accuracies as indicated by high R2 (0.91), low RMSE (0.0197) and low MAE (0.0479). Findings highlight the potential of the ANN as an efficient technique for modeling soil–tool interactions under specific experimental conditions. Such estimations will eventually optimize and enhance the performance efficiency of agricultural implements in the field. Full article
(This article belongs to the Special Issue Engineering of Smart Agriculture—2nd Edition)
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